Quantitative Methods Database - Assignment Example

 Quantitative Database Assignment Introduction This report seeks to undertake an analysis of the housing market for a property development company that is considering building a new housing development in the North Essex area. The areas that are currently under consideration include Colchester, Mersea Island and Jaywick. Some of the key questions the report will respond to include whether there is any difference in the types of homes available in the areas as regards to the type of property and the number of bedrooms amongst others. The report will also analyze how the prices of properties in the areas compare, how the prices of different types of property compare and whether there are any other interesting aspects of the local housing market. Our data included information on the location, the type of houses, the number bedrooms, the price and the parking space. Charts From our analysis, we present different charts that summarize the numerous properties from our data. The first chart presents the standard deviation of the prices of the different types of homes in our areas under study. Standard deviation indicates the degree of variation in the prices of homes. From the analysis, it is evident that highest deviation of prices occurs in the prices of houses between the cities which has a standard deviation of 1.182649718 with the variation in the prices of bungalow being 0.559803074 and 0.245835672. Consequently, the deviation between the different types of homes for Colchester is 1.123087983, 0.337027783 for Jaywick and 1.072970694 for Mersea Island.The deviations in the prices of homes is highest is Colchester. The average prices of the homes indicate that owning a bungalow in all the three areas will cost an average of 0.713536982, while that of a flat is 0.560563004 and that of a house is 1.273070162. Consequently, owning a bungalow will cost a total of 10808630 while it will cost 4408989 for a flat and 36343708 for a house. As regards the average of prices for the different aspects of the different homes, in the case of a bungalow and house, it is evident that having a detached home will cost a grand total of 1.171448428 while the grand total for a mobile home will cost 0.116264276, 0.808875794 for a semi-detached home and 0.615969407 for a terrace home. However, as regards the same, the grand total for owning a bungalow is 0.658932363 while the grand total of owning a house is 1.172291899. As regards the average number of bedrooms, the grand total in the case of Colchester area is 3 while that of Jaywick is 2 and 3 in the case of Mersea Island. Consequently, the average number of bedrooms is 2.6 in the case of bungalow across the areas while being 1.8 and 3.6 in the case of the flat and house across the three areas respectively. Overall, the average is 3 for all the three types of homes across the three cities. Regression Analysis Regression analysis explains the relationship between two variables, the stronger the correlation between variables, the better the prediction. Multiple regression is an important technique that uses several variable to predict values of another variable. From the excel output, the coefficient of the intercept represents the slope which is given by -100,012.3227, this is the point at which the regression line cuts the vertical axis. The 95% confidence interval for the intercept is -163.829.6855 to -36,194.95991 which mean that, based on the sample data the intercept of the population in the three areas is 95% likely to lie in the range of -163,829.6855 to -36,194.95991. On the other hand, the regression coefficient between the numbers of bedrooms in the three areas is 127,792.4504 and this implies that for every increase of 1 in the horizontal axis, the number of bedrooms on the vertical axis change by 127,792.4504. The 95% confidence interval for the number of bedrooms ranges from 108,797.9557 to 146,786.9451. Since the regression analysis is based on the samples from Mersea Island, Jaywick and Colchester and not the total population, there exists a risk that the sample regression coefficient is not the same as that of the population and therefore the 95% confidence interval gives the range of regression slopes within which we are 95% sure that the population slope will lie. From the regression scatter plot, the regression line sloping from bottom left down to top right indicates a negative relationship between the two variables and in regards to the point close to the regression line suggests that the correlation should be a large numerical value and the confidence interval for the slope should be relatively small. The regression line is: Y=-100,012.3227+127,792.4504X where X represents the number of bedrooms in each of the three areas whereas Y is the best predictor of the areas. T-test A t-test is used to determine whether the means of two sets of variables are significantly different from each other. From the excel output, the mean of variable 1 is 149,385.431 and the variance is 7,105,012,996. As for variable 2 the mean is 341,627.3559 while the variance I 78,897,097,995, this implies that the mean for variable 1 is significantly higher than that of variable 2. To test the hypothesis: Ho: Colchester price=Jaywick price H1: Colchester price ≠ Jaywick price The 95% confidence for the difference between the prices of Colchester and Jaywick using a one –tailed t-test is 1.84931E-06 is greater than the t- critical, we reject Ho and conclude that Colchester price is significantly different form Jaywick price. Conclusion From the analysis, it is evident that there isno difference in the types of homes available in the areas, even in aspect like the number of bedrooms with the analysis revealing that the average number of bedrooms being 3. As regards to how the prices of properties in the areas compare, it is evident that while the prices do not significantly differ in between Colchester and Mersea Island, the prices in the two areas significantly differ with the prices for Jaywick. As regards to how the prices of different types of property compare, there is a small difference between the prices of bungalow, flat and house with the price of a house being highest across the three area at 1.27 followed by that of the bungalow at 0.713 and 0.56 for the flat. The most interesting aspects of the local housing market is the fact that in disregard to whether the home is a bungalow or a house, most people prefer a detached type of home. Read More